Instructions to use lsmpp/kontextrefiner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lsmpp/kontextrefiner with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lsmpp/kontextrefiner", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
CogView3PlusTransformer2DModel
A Diffusion Transformer model for 2D data from CogView3Plus was introduced in CogView3: Finer and Faster Text-to-Image Generation via Relay Diffusion by Tsinghua University & ZhipuAI.
The model can be loaded with the following code snippet.
from diffusers import CogView3PlusTransformer2DModel
transformer = CogView3PlusTransformer2DModel.from_pretrained("THUDM/CogView3Plus-3b", subfolder="transformer", torch_dtype=torch.bfloat16).to("cuda")
CogView3PlusTransformer2DModel
[[autodoc]] CogView3PlusTransformer2DModel
Transformer2DModelOutput
[[autodoc]] models.modeling_outputs.Transformer2DModelOutput